Automatically predicting transaction likelihood information and transaction-related temporal information using machine learning techniques
Abstract:
Methods, apparatus, and processor-readable storage media for automatically predicting transaction likelihood information and transaction-related temporal information using machine learning techniques are provided herein. An example computer-implemented method includes obtaining historical data pertaining to completed transactions within an enterprise system; determining, for at least one of the completed transactions, a set of multiple transaction-related features by processing at least a portion of the obtained historical data; training at least one machine learning model using at least a portion of the set of multiple determined transaction-related features; predicting transaction likelihood information and transaction-related temporal information associated with input data attributed to at least one pending transaction within the enterprise system by processing at least a portion of the input data using the at least one machine learning model; and performing one or more automated actions based on one or more of the predicted transaction likelihood information and the predicted transaction-related temporal information.
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